Machine Learning (ML)Responsibilities:
• Develop computer vision systems for enterprises to be used by hundreds of our
customers
• Enhance existing Computer vision systems to achieve high performance
• Prototype new algorithms rapidly, iterating to achieve high levels of performance
• Package these prototypes as robust models written in production level code to be
integrated into the product
• Work closely with the ML engineers to explore and enhance new product features
leading to new areas of business
Requirements:
Strong understanding of linear algebra, optimisation, probability, statistics
• Experience in the data science methodology from exploratory data analysis, feature
engineering, model selection, deployment of the model at scale and model evaluation
• Background in machine learning with experience in large scale training and
convolutional neural networks
• Deep understanding of evaluation metrics for different computer vision tasks
• Knowledge of common architectures for various computer vision tasks like object
detection, recognition, and semantic segmentation
• Experience with model quantization is a plus
• Experience with Python Web Framework (Django/Flask/FastAPI), Machine Learning
frameworks like Tensorflow/Keras/Pytorch
Shubham Vishwakarma
Full Stack Developer - Averlon
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Machine Learning (ML)
Deep Learning
PythonWe're looking for AI/ML enthusiasts who build, not just study. If you've implemented transformers from scratch, fine-tuned LLMs, or created innovative ML solutions, we want to see your work!
What You’ll Do
-Build autonomous AI agents using LangChain, LangGraph, and similar frameworks.
- Develop RAG pipelines with vector DBs like FAISS, Pinecone, or ChromaDB.
- Create FastAPI endpoints to expose agent functionality.
- Implement Model Context Protocol (MCP) for tool-agent integrations.
- Optimize prompts, workflows, and retrieval strategies for real performance.
- Contribute to new agentic AI design patterns and innovations.
Who Should Apply
We’re looking for freshers who are:
-Strong in Python and love experimenting with AI/ML projects.
- Familiar with one or more of these: LangChain/LangGraph, HuggingFace, PyTorch/TensorFlow, RAG pipelines.
- Active on GitHub with 2–3 well-documented projects (clean code + clear README).
- Curious, hands-on builders who want to learn by doing.
Bonus Points if you’ve dabbled with:
- LLM fine-tuning (LoRA, QLoRA), memory systems. AutoGen, CrewAI, MCP, or other agent frameworks.
- Docker, async programming, API integrations.
Education:
- Completed/Pursuing Bachelor's in Computer Science or related field
- Strong foundation in ML theory and practice
Apply if:
- You have done projects using GenAI, Machine Learning, Deep Learning.
- You must have strong Python coding experience.
- Someone who is available immediately to start with us in the office(Hyderabad).
- Someone who has the hunger to learn something new always and aims to step up at a high pace.
We value quality implementations and thorough documentation over quantity. Show us how you think through problems and implement solutions!
Python
PostgreSQLFull-Stack Machine Learning Engineer
Role: Full-Time, Long-Term Required: Python Preferred: C++
OVERVIEW
We are seeking a versatile ML engineer to join as a core member of our technical team. This is a long-term position for someone who wants to build sophisticated production systems and grow with a small, focused team. You will work across the entire stack—from data ingestion and feature engineering through model training, validation, and deployment.
The ideal candidate combines strong software engineering fundamentals with deep ML expertise, particularly in time series forecasting and quantitative applications. You should be comfortable operating independently, making architectural decisions, and owning systems end-to-end.
CORE TECHNICAL REQUIREMENTS
Python (Required): Professional-level proficiency writing clean, production-grade code—not just notebooks. Deep understanding of NumPy, Pandas, and their performance characteristics. You know when to use vectorized operations, understand memory management for large datasets, and can profile and optimize bottlenecks. Experience with async programming and multiprocessing is valuable.
Machine Learning (Required): Hands-on experience building and deploying ML systems in production. This goes beyond training models—you understand the full lifecycle: data validation, feature engineering, model selection, hyperparameter optimization, validation strategies, monitoring, and maintenance.
Specific experience we value: gradient boosting frameworks (LightGBM, XGBoost, CatBoost), time series forecasting, probabilistic prediction and uncertainty quantification, feature selection and dimensionality reduction, cross-validation strategies for non-IID data, model calibration.
You should understand overfitting deeply—not just as a concept but as something you actively defend against through proper validation, regularization, and architectural choices.
Data Pipelines (Required): Design and implement robust pipelines handling real-world messiness: missing data, late arrivals, schema changes, upstream failures. You understand idempotency, exactly-once semantics, and backfill strategies. Experience with workflow orchestration (Airflow, Prefect, Dagster) expected. Comfortable with ETL/ELT patterns, incremental vs full recomputation, data quality monitoring, database design and query optimization (PostgreSQL preferred), time series data at scale.
C++ (Preferred): Experience valuable for performance-critical components. Writing efficient C++ and interfacing with Python (pybind11, Cython) is a significant advantage.
HIGHLY DESIRABLE: MULTI-AGENT ORCHESTRATION
We are building systems leveraging LLM-based automation. Experience with multi-agent frameworks highly desirable: LangChain, LangGraph, or similar agent frameworks; designing reliable AI pipelines with error handling and fallbacks; prompt engineering and output parsing; managing context and state across agent interactions. You do not need to be an expert, but genuine interest and hands-on experience will set you apart.
DOMAIN EXPERIENCE: FINANCIAL DATA AND CRYPTO
Preference for candidates with experience in quantitative finance, algorithmic trading, or fintech; cryptocurrency markets and their unique characteristics; financial time series data and forecasting systems; market microstructure, volatility, and regime dynamics. This helps you understand why reproducibility is non-negotiable, why validation must account for temporal structure, and why production reliability cannot be an afterthought.
ENGINEERING STANDARDS
Code Quality: Readable, maintainable code others can modify. Proper version control (meaningful commits, branches, code review). Testing where appropriate. Documentation: docstrings, READMEs, decision records.
Production Mindset: Think about failure modes before they happen. Build in observability: logging, metrics, alerting. Design for reproducibility—same inputs produce same outputs.
Systems Thinking: Consider component interactions, not just isolated behavior. Understand tradeoffs: speed vs accuracy, flexibility vs simplicity. Zoom between architecture and implementation.
WHAT WE ARE LOOKING FOR
Self-Direction: Given a problem and context, you break it down, identify the path forward, and execute. You ask questions when genuinely blocked, not when you could find the answer yourself.
Long-Term Orientation: You think in years, not months. You make decisions considering future maintainability.
Intellectual Honesty: You acknowledge uncertainty and distinguish between what you know versus guess. When something fails, you dig into why.
Communication: You explain complex concepts clearly and document your reasoning.
EDUCATION
University degree in a quantitative/technical field preferred: Computer Science, Mathematics, Statistics, Physics, Engineering. Equivalent demonstrated expertise through work also considered.
TO APPLY
Include: (1) CV/resume, (2) Brief description of a production ML system you built, (3) Links to relevant work if available, (4) Availability and timezone.
Machine Learning (ML)Job Description – Machine Learning Expert
Role: Machine Learning Expert
Experience: 6+ Years
Location: Bangalore
Education: B.Tech Degree (Computer Science / Information Technology / Data Science / related fields)
Work Mode: Hybrid – 3 Days Office + 3 Days Work from Home
Interview Mode: Candidate must be willing to attend Face-to-Face (F2F) L2 round at Bangalore location
About the Role
We are seeking a highly skilled Machine Learning Expert with a strong background in building, training, and deploying AI/ML models. The ideal candidate will bring hands-on expertise in designing intelligent systems that leverage advanced algorithms, deep learning, and data-driven insights to solve complex business challenges.
Key Responsibilities
- Develop and implement machine learning and deep learning models for real-world business use cases.
- Perform data cleaning, preprocessing, feature engineering, and model optimization.
- Research, design, and apply state-of-the-art ML techniques across domains such as NLP, Computer Vision, or Predictive Analytics.
- Collaborate with data engineers and software developers to ensure seamless end-to-end ML solution deployment.
- Deploy ML models to production environments and monitor performance for scalability and accuracy.
- Stay updated with the latest advancements in Artificial Intelligence and Machine Learning frameworks.
Required Skills & Qualifications
- B.Tech degree in Computer Science, Information Technology, Data Science, or related discipline.
- 6+ years of hands-on experience in Machine Learning, Artificial Intelligence, and Deep Learning.
- Strong expertise in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras.
- Solid foundation in mathematics, statistics, algorithms, and probability.
- Experience in working with NLP, Computer Vision, Recommendation Systems, or Predictive Modeling.
- Knowledge of cloud platforms (AWS / GCP / Azure) for model deployment.
- Familiarity with MLOps tools and practices for lifecycle management.
- Excellent problem-solving skills and the ability to work in a collaborative environment.
Preferred Skills (Good to Have)
- Experience with Big Data frameworks (Hadoop, Spark).
- Exposure to Generative AI, LLMs (Large Language Models), and advanced AI research.
- Contributions to open-source projects, publications, or patents in AI/ML.
Work Mode & Interview Process
- Hybrid Model: 3 days in office (Bangalore) + 3 days remote.
- Interview: Candidate must be available for Face-to-Face L2 interview at Bangalore location.
Javascript
Amazon Web Services (AWS)
DockerMachine Learning (ML)Responsibilities:
● Design, develop, and maintain scalable backend services and APIs using Java and Spring
Boot.
● Create and optimize SQL database schemas and queries in PostgreSQL to ensure efficient
data storage and retrieval.
● Implement RESTful APIs to facilitate seamless communication between frontend and backend
components.
● Configure and manage Nginx web servers to efficiently handle incoming requests and improve
application performance.
● Deploy and manage applications on AWS or GCP, ensuring scalability, reliability, and
security.
● Configure and optimize message broker systems using Kafka for real-time data processing
and communication.
● Containerize applications using Docker for easy deployment, scaling, and management.
● Create detailed Low-Level Designs (LLDs) and High-Level Designs (HLDs) to guide the
development and architecture of backend systems.
● Automating CI/CD pipelines and streamlining the software development lifecycle.
● Integrate AI/ML models into backend workflows using Python, PyTorch/TensorFlow, or
third-party AI APIs.
● Leverage AI tools (e.g., OpenAI APIs, Hugging Face, AWS AI services) to build intelligent
features.
● Collaborate closely with frontend developers, product managers, data scientists, and other
stakeholders to deliver high-quality AI-powered solutions.
● Monitor and troubleshoot production systems to ensure optimal performance, reliability, and
uptime.
What We’re Looking For:
● Bachelor’s degree in Computer Science, Engineering, or related field.
● 3-5 years of experience in backend development.
● Proficiency in Java, Spring Boot, PostgreSQL, SQL, and GitActions.
● Strong understanding of RESTful API design principles and best practices.
● Experience with configuring and optimizing Nginx web servers.
● Experience with configuring and optimizing Kafka service.
● Hands-on experience with AWS or GCP.
● Familiarity with Docker containers and container orchestration.
● Ability to create comprehensive Low-Level Designs (LLDs) and High-Level Designs (HLDs)
for backend systems.
● Experience with Python for AI/ML model integration in backend services.
● Familiarity with AI platforms and APIs such as OpenAI, Hugging Face, AWS AI/ML, or GCP
Vertex AI.
● Excellent problem-solving skills and attention to detail.
● Strong communication and collaboration skills, with the ability to work effectively in a team
environment.
Preferred Qualifications:
● Knowledge of microservices architecture and related technologies.
● Experience with cloud-native development and serverless computing.
● Understanding of software development best practices, including Agile methodologies
Python
DjangoYour responsibilities as a backend engineer will include:
- Back-end software development
- Software engineering and designing data models and write effective APIs
- Working together with engineers and product teams
- Understanding business use cases and requirements for different internal teams
- Maintenance of existing projects and New feature development
- Consume and integrate classifier/ ML snippets from Data science team
What we are looking for:
- 2+ years of industry experience with the Python and Django framework.
- Degree in Computer Science or related field
- Good analytical skills with strong fundamentals of data structures and algorithms
- Experience building backend services with hands-on experience through all stages of Agile software development life cycle.
- Ability to write optimized codes,debug programs, and integrate applications with third party tools by developing various APIs
- Experience with Databases.
- Experience with writing REST-APIs.
- Prototyping initial collection and leveraging existing tools and/or creating new tools
- Experience working different types of datasets (e.g. unstructured, semi-structured, with missing information)
- Ability to think critically and creatively in a dynamic environment, while picking up new tools and domain knowledge along the way
- A positive attitude, and a growth mindset
Bonus:
- Experience with relevant Python libraries such as Requests, sklearn, Selenium
- Hands on experience in Machine learning implementations
- Experience with Cloud infrastructure (e.g. AWS) and relevant microservices
- Good Humor
Note- We are currently working from home due to the pandemic. If selected you may work from a remote location though once office reopens candidate must work from Office.
PythonDjangoMachine Learning (ML)Positions : 2-3
CTC Offering : 40,000 to 55,000/month
Job Location: Remote for 6-12 months due to the pandemic, then Mumbai, Maharashtra
Required experience:
Minimum 1.5 to 2 years of experience in Web & Backend Development using Python and Django with experience in some form of Machine Learning ML Algorithms
Overview
We are looking for Python developers with a strong understanding of object orientation and experience in web and backend development. Experience with Analytical algorithms and mathematical calculations using libraries such as Numpy and Pandas are a must. Experience in some form of Machine Learning. We require candidates who have working experience using Django Framework and DRF
Key Skills required (Items in Bold are mandatory keywords) :
1. Proficiency in Python 3.x based web and backend development
2. Solid understanding of Python concepts
3. Strong experience in building web applications using Django
4. Experience building REST APIs using DRF or Flask
5. Experience with some form of Machine Learning (ML)
6. Experience in using libraries such as Numpy and Pandas
7. Some form of experience with NLP and Deep Learning using any of Pytorch, Tensorflow, Keras, Scikit-learn or similar
8. Hands on experience with RDBMS such as Postgres or MySQL
9. Comfort with Git repositories, branching and deployment using Git
10. Working experience with Docker
11. Basic working knowledge of ReactJs
12. Experience in deploying Django applications to AWS,Digital Ocean or Heroku
KRAs includes :
1. Understanding the scope of work
2. Understanding and adopting the current internal development workflow and processes
3. Understanding client requirements as communicated by the project manager
4. Arriving on timelines for projects, either independently or as a part of a team
5. Executing projects either independently or as a part of a team
6. Developing products and projects using Python
7. Writing code to collect and mathematically analyse large volumes of data.
8. Creating backend modules in Python by building or reutilizing existing modules in a manner so as to provide optimal deliveries on time
9. Writing Scalable, maintainable code
10. Building secured REST APIs
11. Setting up batch task processing environments using Celery
12. Unit testing prepared modules
13. Bug fixing issues as reported by the QA team
14. Optimization and performance tuning of code
Bonus but not mandatory
1. Nodejs
2. Redis
3. PHP
4. CI/CD
5. AWS
Python
JavaMachine Learning (ML)
Data Science
ScalaJava
.NETAmazon Web Services (AWS)PythonJavaPythonJavascriptAmazon Web Services (AWS)
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon